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219
Voted
CVPR
2003
IEEE
16 years 9 months ago
2003
IEEE
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...
224
Voted
CVPR
2005
IEEE
16 years 9 months ago
2005
IEEE
We propose a generative model that codes the geometry and appearance of generic visual object categories as a loose hierarchy of parts, with probabilistic spatial relations linkin...
181
Voted
CVPR
2006
IEEE
16 years 9 months ago
2006
IEEE
Simultaneous localisation and mapping using a single camera becomes difficult when erratic motions violate predictive motion models. This problem needs to be addressed when visual...
185
Voted
CVPR
2007
IEEE
16 years 9 months ago
2007
IEEE
Current methods for learning visual categories work well when a large amount of labeled data is available, but can run into severe difficulties when the number of labeled examples...
156
Voted
CVPR
2007
IEEE
16 years 9 months ago
2007
IEEE
In this paper, we address two closely related visual tracking problems: 1) localizing a target's position in low or moderate resolution videos and 2) segmenting a target'...